Run AI at scale. without losing sleep over it.
For CTOs and engineering leaders shipping AI in production. We are already handling millions of requests across hundreds of teams, with security and uptime that keep your platform online while you scale.
600+ MODELS · ONE API · TRUSTED BY TEAMS SHIPPING AI IN PRODUCTION
Run safely. Don't crash.
The two things every CTO worries about when AI moves to production: a security gap that surfaces in an audit, or a provider outage that takes the whole product down. each::labs is built so neither happens to you.
Won't crash on a bad provider day
Quality aware failover catches degradations on every call. When Kling 503s or Veo slows to a crawl, traffic spills to a healthy fallback in under 120ms, before your users notice.
Won't leak through a security gap
Zero retention by default. Provider side retention disabled per request. We never train on your traffic. Your prompts and outputs stay where you need them, nowhere else.
Won't blow your budget without warning
Per call traces tag every request with cost, latency, and the attributes you care about. Finance gets the answer to "who is expensive" without a quarterly instrumentation sprint.
Consumer apps with millions of users, ad tech platforms running billion+ monthly requests, and enterprise platforms with strict change control are all on the same router.
Scate
Byterise
PixelByte
Yoya Mobile
Pixel Wizard
baby.ai
Kata Technology
Wask
JoyoLabs
MobileOceanScateByterisePixelByteYoya MobilePixel Wizardbaby.aiKata TechnologyWaskJoyoLabsMobileOceanScateByterisePixelByteYoya MobilePixel Wizardbaby.aiKata TechnologyWaskJoyoLabsMobileOceanEnterprise features. Built around how teams actually run AI in production.
Team budget management
Set monthly inference budgets per team, per project, or per environment. Alert thresholds, hard caps, and rollovers, all enforced at the router so finance never gets surprised.
24/7 contact with engineering
Direct Slack channel with the engineers who built the router. P1 issues acknowledged the same business day; on call coverage 24/7/365, not "business hours in our timezone."
Dedicated customer success manager
A named CSM assigned at signing, walks your team through onboarding, traffic design, and quarterly business reviews. Direct input on roadmap.
Custom volume pricing
Commit to monthly inference volume and the platform fee drops. Provider price is still provider price. Zero markup on inference, ever.
Zero retention by default
We don't store prompts or outputs past what you opt into for traces. Provider side retention disabled per provider. We never train on your traffic.
Quarterly business reviews
Scheduled QBR with your CSM and a senior engineer. Cost trends, failover patterns, model swap opportunities, and what is shipping next quarter on our side.
Procurement docs, one email away.
We don't hide the paperwork behind a sales call. Email the engineering team, your security or legal counterpart gets a direct reply, usually same business day.
Sub processor list
Current providers and their role · updated as we add models
Request via engineeringUptime + incident process
How we run on call, what counts as a P1, and how we report it
Request via engineeringNOTHING HERE IS BEHIND "JUMP ON A QUICK CALL." YOUR PROCUREMENT TEAM IS WELCOME.
FAQ
the questions every CTO asks before signing
What uptime does each::labs Enterprise offer?
Get on a call with the team building this.
The first call is with a senior engineer who reviews your architecture, your traffic shape, and your scale targets. They will quote a deployment model and a price. If we cannot help, we say so on the call.